In modern society, the use of industrial automation equipment is increasing. More and more enterprises, businesses and customers are choosing to use mechanical equipment, which can not only increase productivity but also reduce people's burden and allow for long-term uninterrupted work. Today we are going to learn about machine vision equipment. Do you know how vision equipment works?
Machine vision systems utilize machines to perform various measurements and judgments, replacing human eyes. It is an important branch of computer science, integrating technologies from optics, mechanics, electronics, and computer hardware and software, involving multiple fields such as computer science, image processing, pattern recognition, artificial intelligence, signal processing, and opto-mechatronics. The rapid development of technologies such as image processing and pattern recognition has also greatly promoted the development of machine vision.
Using machine vision equipment means replacing human eyes with machines to complete inspections. Specifically, the process involves using an industrial camera to capture images of the device being inspected. This acquisition process is arguably the most crucial part of machine vision because it requires capturing all the features that need to be detected in the device. Therefore, image acquisition requires continuous adjustment of the light source and camera parameters based on the characteristics of the device to ensure accurate image acquisition.
At this point, the signal is analog. Then, professional image processing software is used to convert the analog signal into a digital signal. The signal is then processed to extract the target's features to be detected, such as color, whether there are scratches on the surface of the device, whether the size is up to standard, whether the surface coating is uniform, etc. The output results are fed back to the mechanical end to sort the devices and pick out the unqualified devices.
Generally, machine vision equipment works by combining robot vision hardware into two main parts: image acquisition and visual processing. Image acquisition consists of a lighting system, a vision sensor, an analog -to- digital converter, and a frame buffer. Robot vision acquires two-dimensional images of the environment through vision sensors, analyzes and interprets them through a vision processor, and then converts them into symbols, enabling the robot to recognize objects and determine their locations.
